eval-performance

eval-performance is a skill for Claude Code from F-U-S-E-E/FuseDevelopmentGroup. It costs 180 tokens per session (1,065 once invoked), scanned A, original, AGPL-3.0.

A guide to finding slow MSBuild project evaluation. Project evaluation is the build stage that reads project files and imports before compilation begins.

In plain words
What is it for?
Use it to investigate slow .NET or MSBuild startup time, including costly directory patterns and deep import chains.
Why use it?
It helps explain delays caused by large file searches, many imports, or expensive build configuration.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/f-u-s-e-e/fusedevelopmentgroup/eval-performance
Any agent
npx skills add F-U-S-E-E/FuseDevelopmentGroup --skill eval-performance
Clone the repo
git clone --depth 1 https://github.com/F-U-S-E-E/FuseDevelopmentGroup

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for eval-performance

README.md
[![agentmods](https://agentmods.dev/badge/skills/f-u-s-e-e/fusedevelopmentgroup/eval-performance.svg)](https://agentmods.dev/skills/f-u-s-e-e/fusedevelopmentgroup/eval-performance)
Your own site
<a href="https://agentmods.dev/skills/f-u-s-e-e/fusedevelopmentgroup/eval-performance"><img src="https://agentmods.dev/badge/skills/f-u-s-e-e/fusedevelopmentgroup/eval-performance.svg" alt="Measured on agentmods" height="20"></a>
Per session 180 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,065 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00180 $0.01065
Opus 5 $0.00090 $0.00532
Sonnet 5 $0.00036 $0.00213
Haiku 4.5 $0.00018 $0.00106

Measured 2d ago against content hash 592477a039ea, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

eval-performance scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/eval-performance/SKILL.md · 89 lines

The source is not reproduced here

Licensed AGPL-3.0

The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 89 lines · 180 tokens per session scan A 592477a039ea

Subscribe to this mod's changes

eval-performance is a skill published in the GitHub repository F-U-S-E-E/FuseDevelopmentGroup (22 stars, last pushed 12d ago), licensed AGPL-3.0. It adds 180 tokens to every session and 1,065 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

debug-optimize-lcp

Guides debugging and optimizing Largest Contentful Paint (LCP) using Chrome DevTools MCP tools. Use this skill whenever the user asks about LCP performance, slow page loads, Core Web Vitals optimization, or wants to understand why their page's main content takes too long to appear. Also use when the user mentions…

ChromeDevTools/chrome-devtools-mcp · 99 tokens

systematic-debugging

Use when debugging a failing test, build error, or runtime issue that isn't immediately obvious. Guides a 4-phase root cause analysis instead of random fix attempts.

open-metadata/OpenMetadata · 37 tokens

diagnose

Trace from a reproduced symptom to the source code that causes it. Pin the specific file and approximate line, rate confidence in the cause and clarity of the fix independently, and always propose a concrete fix.

emdash-cms/emdash · 43 tokens

azsdk-common-pipeline-analysis

Analyze Azure SDK CI/CD pipeline failures into a structured diagnosis, and define the required output format. Load this skill before calling azsdkanalyzepipeline, which returns raw failure data that this skill interprets and formats. USE FOR: "pipeline failed", "build failure", "CI check failing", "tests failing in…

Azure/azure-sdk-for-net · 192 tokens

repro-admin

Reproduce an EmDash admin UI bug. Attach a container, start the demo dev server, drive the admin with agent-browser using the dev-bypass session, and capture the reproduction as screenshots plus a replayable transcript.

emdash-cms/emdash · 48 tokens

log-error-digest

Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or…

zebbern/claude-code-guide · 71 tokens